Digital images can be stored in user's computers and viewed on electronic display devices. The proliferation of mobile devices has enabled users to take pictures, share photos, and post photos online. Digital images can be uploaded to and stored at a central network location. Users can store, organize, edit, enhance, and share digital images using web browsers or mobile applications. Users can also design and personalize image products such as image prints, photo books, photo calendars, photo greeting cards, holiday cards, photo stationeries, photo mugs, and photo T-shirts, which incorporate users' digital images.
Handling a large number of digital images has become a challenge and an obstacle to the utilizations of images. As mobile phones and digital cameras have made photo taking very convenient, people often snap many pictures of the same scene at each moment especially if it is a special occasion. These pictures tend to be similar to each other, comprising people having similar facial expressions. The current image software usually display all the captured images on devices, which can be overwhelming for viewing, editing, and using in product design or electronic sharing. Users have to carefully compare these similar photos, remove most of them, and keep one or a few for display for each set of people at each scene. Picking photos with the best facial expressions may require examining the photos at higher image magnifications. As a result, selecting photos is often the most time consuming task for creating personalized image products.
Furthermore, in professional photo shooting at schools, sports events, churches, or studios etc., a photographer often takes a series of photos of one or more persons, and then manually picks the photo having the best facial expression(s) (e.g. smiles) for printing. In case a satisfactory photo is not found, the photographer may need to retake the photos or even reschedule the photo-shooting event.
There is therefore a need for an automated method to accurately recognize facial expressions in digital images. There is also a need to help photographers and others to determine quickly if a group of recently taken photos includes at least one photo that meets pre-defined quality criteria. In addition to image selection and photo-product designs, facial expression recognition also has applications in photo posting and sharing, medicine, entertainment, law, and marketing.